Agentic Engineer/Software Developer

Edgesource Corporation•Alexandria, VA

2d•Hybrid

About The Position

We are seeking a highly motivated Mid-to-Senior Applications & Systems Engineer to design, develop, integrate, and sustain modern software applications, cloud services, and mission-critical systems. The ideal candidate is a hands-on engineer with experience building full-stack applications, automating operational workflows, integrating complex systems, and leveraging modern AI-powered development tools and agentic workflows to accelerate delivery. This position requires an engineer who can operate across traditional boundaries between software engineering, systems engineering, cloud infrastructure, DevOps, and AI-enabled automation. The successful candidate will help architect and implement scalable solutions while identifying opportunities to apply AI agents, automation frameworks, and intelligent workflows to improve operational efficiency and software delivery.

Requirements

Active Top Secret clearance with SCI eligibility
Bachelor’s degree in Computer Science, Software Engineering, Systems Engineering, Information Systems, or related field (or equivalent experience).
5+ years of experience in software engineering, systems engineering, or application development.
Experience with one or more programming languages such as Python, JavaScript/TypeScript, Go, Java, PHP, or C#.
Experience designing and consuming REST APIs and service-based architectures.
Experience with cloud platforms such as AWS or Microsoft Azure.
Experience with CI/CD pipelines, source control, and modern software development practices.
Strong troubleshooting and problem-solving skills.
Ability to work independently and collaboratively in Agile environments.

Nice To Haves

Experience building or integrating AI-powered applications and agentic workflows.
Experience with LLM platforms such as OpenAI, Anthropic Claude, Azure OpenAI, or similar technologies.
Familiarity with AI orchestration frameworks, RAG architectures, vector databases, and workflow automation platforms.
Experience with Databricks, data lakes, or large-scale analytics environments.
Experience with containerization and orchestration technologies.
Experience supporting government, defense, intelligence community, or regulated environments.
Familiarity with cybersecurity, secure software development, or RMF principles.
Experience supporting real-time, mission-critical, or operational systems.

Responsibilities

Design, develop, test, and maintain web applications, APIs, microservices, and backend systems.
Build scalable and maintainable software solutions using modern programming languages and frameworks.
Develop and integrate RESTful APIs, event-driven architectures, and asynchronous processing systems.
Participate in application modernization, refactoring, and technical debt reduction initiatives.
Troubleshoot and resolve production issues across application and infrastructure layers.
Analyze user requirements and translate operational needs into technical solutions.
Design and integrate complex systems spanning cloud, on-premises, and hybrid environments.
Support system architecture development, interface definition, and technical documentation.
Perform system validation, testing, and performance optimization.
Collaborate with stakeholders, product owners, and engineering teams throughout the system lifecycle.
Design and implement AI-assisted workflows that improve engineering productivity and operational effectiveness.
Develop agentic solutions using modern LLM platforms, orchestration frameworks, and automation tools.
Build AI-powered assistants for software development, data processing, system operations, and business workflows.
Evaluate and integrate AI coding assistants, autonomous agents, and workflow automation technologies.
Identify opportunities to automate repetitive engineering and operational tasks using AI-enabled solutions.
Develop and maintain CI/CD pipelines and automated deployment processes.
Support cloud-native solutions across AWS, Azure, and hybrid environments.
Implement containerized solutions using Docker and related technologies.
Automate infrastructure provisioning, configuration management, and operational monitoring.
Support application security, reliability, scalability, and observability initiatives.
Build and maintain data ingestion, transformation, and processing pipelines.
Support integration of structured and unstructured data sources.
Develop automation for data movement, validation, and analytics workflows.
Collaborate with data engineers, analysts, and AI/ML teams to support mission and business objectives.